Quantitative and Qualitative Pain Evaluation in Response to OnabotulinumtoxinA for Chronic Migraine: An Observational Real-Life Study
Bibliographic record
Abstract
(1) Background: Randomized controlled trials and real-life studies demonstrated the efficacy of OnabotulinumtoxinA (OBT-A) for CM prevention. However, no studies specifically addressed its effect on pain’s quantitative intensity and qualitative characteristics. (2) Methods: This is an ambispective study: a post-hoc retrospective analysis of real-life prospectively collected data from two Italian headache centers on CM patients treated with OBT-A over one year (i.e., Cy1-4). The primary endpoint was the changes in pain intensity (Numeric Rating Scale, NRS; the Present Pain Intensity (PPI) scale, the 6-point Behavioral Rating Scale (BRS-6)) and quality scale (the short-form McGill Pain Questionnaire (SF-MPQ)) scores. We also assessed the relationship between changes in intensity and quality of pain and disability scale (MIDAS; HIT-6) scores, monthly headache days (MHDs), and monthly acute medication intake (MAMI) (3) Results: We retrieved 152 cases (51.5 years SD 11.3, 80.3% females). From baseline to Cy-4, MHDs, MAMI, NRS, PPI, and BRS-6 scores decreased (consistently p < 0.001). Only the throbbing (p = 0.004), splitting (p = 0.018), and sickening (p = 0.017) qualities of pain collected in the SF-MPQ were reduced. Score variations in MIDAS related to those in PPI scales (p = 0.035), in the BRS-6 (p = 0.001), and in the NRS (p = 0.003). Similarly, HIT-6 score changes related to PPI score modifications (p = 0.027), in BRS-6 (p = 0.001) and NRS (p = 0.006). Conversely, MAMI variation was not associated with qualitative or quantitative pain score modifications except BRS-6 (p = 0.018). (4) Conclusions: Our study shows that OBT-A alleviates migraine by reducing its impact on multiple aspects, such as frequency, disability, and pain intensity. The beneficial effect on pain intensity seems specific to pain characteristics related to C-fiber transmission and is associated with a reduction in migraine-related disability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".